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Steering language generation towards objectives or away from undesired content has been a long-standing goal in utilizing language models (LM).
Language models are few-shot learners
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Fine-tuning language models from human preferences
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
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Plug and play language models: A simple approach to controlled text generation
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Policy gradient methods for reinforcement learning with function approximation
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Variance reduction techniques for gradient estimates in reinforcement learning
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Don’t stop pretraining: adapt language models to domains and tasks
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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
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Gedi: Generative discriminator guided sequence generation
Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, and Nazneen Fatema Rajani. 2020 · 2009
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A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and Bill Dolan. 2015 · 2015
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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2015 · 2015
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High-dimensional continuous control using generalized advantage estimation
John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel. 2015 · 2015
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An actor-critic algorithm for sequence prediction
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Google’s neural machine translation system: Bridging the gap between human and machine translation
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Hafez: an interactive poetry generation system
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Deceiving google’s perspective api built for detecting toxic comments
Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano. 2020 · 2020
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Text generation with efficient (soft) q-learning
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Gpt-critic: Offline reinforcement learning for end-to-end task-oriented dialogue systems
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Boseop Kim, HyoungSeok Kim, Sang-Woo Lee, Gichang Lee, Donghyun Kwak, Dong Hyeon Jeon, Sunghyun Park, Sungju Kim, Seonhoon Kim, Dongpil Seo, et al. 2021 · 2021
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Controlled text generation as continuous optimization with multiple constraints
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Hossein Hosseini, Sreeram Kannan, Baosen Zhang, and Radha Poovendran. 2017 · 2017
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Toward controlled generation of text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017 · 2017
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Reinforcement learning for bandit neural machine translation with simulated human feedback
Khanh Nguyen, Hal Daumé III, and Jordan Boyd-Graber. 2017 · 2017
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A deep reinforced model for abstractive summarization
Romain Paulus, Caiming Xiong, and Richard Socher. 2017 · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
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Learning to write with cooperative discriminators
Ari Holtzman, Jan Buys, Maxwell Forbes, Antoine Bosselut, David Golub, and Yejin Choi. 2018 · 2018
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Dexperts: Decoding-time controlled text generation with experts and anti-experts
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A Smith, and Yejin Choi. 2021 · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al. 2021 · 2021
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Towards facilitating empathic conversations in online mental health support: A reinforcement learning approach
Ashish Sharma, Inna W Lin, Adam S Miner, David C Atkins, and Tim Althoff. 2021 · 2021
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Recursively summarizing books with human feedback
Jeff Wu, Long Ouyang, Daniel M Ziegler, Nisan Stiennon, Ryan Lowe, Jan Leike, and Paul Christiano. 2021 · 2021
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FUDGE: Controlled text generation with future discriminators
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Director: Generator-classifiers for supervised language modeling
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A distributional lens for multi-aspect controllable text generation
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Offline rl for natural language generation with implicit language q learning
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Efficient reinforcement learning for unsupervised controlled text generation
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Off-policy deep reinforcement learning without exploration
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